(1) Field of the Invention
The present invention generally relates to a system and method for detecting and time-tagging surface impact acoustic signatures, and more particularly to a soft impact location capability (SILC) system and method incorporating real-time polyphase digital signal processing for detecting and time-tagging surface impact acoustic signatures.
(2) Description of the Background
Acoustic tracking may be utilized for tracking and studying a variety of marine subjects including aquatic life, seismic phenomena, and man-made objects such as submarines, underwater munitions, etc. There are numerous different types of acoustic tracking arrays. FIG. 1 shows the SILC system, each acoustic sensor 10 is moored to the ocean bottom 12 and is individually cabled 14 to its own surface buoy 16. Each buoy 16 contains a surface float 18, digital signal processing (DSP) system 20, a radio link 22, and bottom-mounted acoustic sensors 10, called hydrophones, which receive acoustic waves. Acoustic tracking arrays can be used for detecting the “soft-impacts” of long-range munitions 24. Specifically, when munitions are fired they travel a distance before impacting the ocean surface 26. As these projectiles 24 hit the surface, the impact acoustic signature 28 propagates through the water and is detected by sensors 10 associated with the multiple buoys 16. The hydrophone signal is converted from analog to digital form in a DSP 20 located in the buoy 16. The DSP system 20 processes the impact signature and then sends the time tagged detections to a tracking and display computer 30 via a radio link 22. Data from multiple buoys is utilized to determine the water surface location and impact time of the projectile. The tracking and display computer 30 is joined to a radio receiver and located on a remote platform. The remote platform can be on land, at sea or in air.
FIG. 2 shows a block diagram of a previous embodiment of a multi-band detector. The multi-band detector 32 is realized as software on DSP 20. Multi-band detector 32 includes a plurality of single band detectors 34. The single band detector 34 essentially measures the energy in the band of frequencies delivered within a specified time window. Each single-band detector 34 is a one-channel non-coherent bandpass detector, comprising a bandpass filter 36, a software squaring routine 38, a boxcar filter 40, a thresholding module 42 and a detection analyzer 44. Each input signal x(n) is passed through a bandpass filter 36, which allows a specific band of frequencies to pass and eliminates or attenuates other frequencies. The band of frequencies to be examined is determined by the bandpass filter center frequency ωo and bandwidth B. The frequencies are then squared ( )2 by a software squaring routine 38 and then transferred to a boxcar filter 40 for further signal processing.
The boxcar filter 40 (or sliding average filter) is a lowpass filter with a rectangle-shaped impulse response (akin to a box, hence the name) that passes low frequencies, and eliminates or attenuates high frequencies. This can be implemented with a suitable Finite Impulse Response (FIR) filter with unit-valued coefficients. The filter 40 processes each channel separately to detect if an impact occurred. The boxcar lowpass filter 40 has an impulse response b(n)=1, for n=0, 1, . . . , MB−1 and b(n)=0 elsewhere. The boxcar filter 40 output, z(n), is the integrated energy over the most recent MB samples of its input signal.
A thresholding module 42 examines the boxcar filter output and provides an indication whether an impact occurred on the ocean surface 26. When the measured energy of a signal output from a boxcar filter 40 exceeds the detection threshold t, a detection is registered with a logic and time-stamp module 44. The detection threshold t is chosen proportional to a measured noise power level, so that a constant false-alarm rate is achieved. In signal detection theory, a false alarm occurs where a non-target event exceeds the detection criterion and is identified as a target. The threshold is:t=k N2,  (1)where the term N2 represents the noise power level, which is continuously calculated by a separate system. The separate system squares each incoming value and then averages the sum of the squares (divide by n) to calculate N2. The term k is the threshold multiplier and is calculated by obtaining the false alarm rate curves which allow the system operator to select k to provide the desired false alarm rate. Thus, when a signal exceeds the detection threshold t=k N2, a detection is registered, and information regarding the shape of the detected pulse is extracted. This information includes the time of arrival (TOA), pulse strength, and pulse duration. The pulse time of arrival (TOA) is estimated by finding the time corresponding to the peak change in the boxcar output over the detection period. That is, if z(n) denotes the boxcar filter output, the change in the filter output is given by:
      Δ    ⁢                  ⁢          z      ⁡              (        n        )              =            z      ⁡              (        n        )              -                  z        ⁡                  (                      n            -                          M              B                                )                    .      The value of Δz(n) is monitored over the detection period, and the time index at which Δz(n) achieves its peak is reported at the pulse TOA. The pulse strength for the detection is the peak value of the signal z(n) over the detection period. The end of the detection is declared when the boxcar filter output z(n) drops below a second user specified threshold k2 N2, where k2 is chosen to be less than k.
Logic and time-stamp module 44 combines the detection and TOA results from the single-band detectors 34 to identify a broad-band event. Once a detector 34 produces a detection, other single-band detectors 34 are examined to see if additional detections exist. For a broad-band detection to be reported, several individual detection bands must report detections within a user-specified maximum inter-band timing skew (MITS) time window. Otherwise, the detection information is discarded as a narrow-band false alarm. Also, for each broad-band detection report, the reported TOA is the average of TOA values from the individual bands. The reported pulse width is the longest pulse width over all detection bands.
To detect gunfire impacts, which are typically broad-band events, previous impact systems incorporating DSP algorithms implemented multiple narrow-band detectors, each examining a separate frequency band. This prior art approach suffers from a number of drawbacks including the large computational requirements for real-time operation. Additionally, many channels are required to monitor a wide range of frequencies, making it impractical for use in tracking soft impacts from a wide range of munitions types.
Thus it would be greatly advantageous to provide a soft impact location system which: (1) incorporates a computationally efficient real-time polyphase digital signal-processing (DSP) algorithm, (2) processes wide-band acoustic munition signatures, (3) monitors the entire Nyquist frequency band for energy, (4) has parameter flexibility (maximum inter-band timing skew or “MITS”, number of frequencies required for a detection, etc.), (5) allows users to tailor the DSP algorithm to accommodate many different testing environments and munition types, (6) utilizes software that simulates the DSP algorithm and estimates performance.